Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Running sum: SELECT id, amount, SUM(amount) OVER (ORDER BY id) running_sum FROM t. With partition: SUM(amount) OVER (PARTITION BY customer_id ORDER BY date). Unbounded preceding to current row is default. For last N rows: ROWS BETWEEN N PRECEDING AND CURRENT ROW. **Why it...
Running sum: SELECT id, amount, SUM(amount) OVER (ORDER BY id) running_sum FROM t. With partition: SUM(amount) OVER (PARTITION BY customer_id ORDER BY date). Unbounded preceding to current row is default. For last N rows: ROWS BETWEEN N PRECEDING AND CURRENT ROW. Why it matters: Design choices compound at scale—wrong approach can cause 100× overhead. Scalability trade-offs: Profile before optimizing; validate on sample then full. Cost implications: Suboptimal choices multiply at billion-row scale.
Red Flag: Generic textbook answers. Pro-Move: 'At scale we measured X, implemented Y, achieved Z%—validated and iterated.'
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